RAPSearch2: a fast and memory-efficient protein similarity search tool for next-generation sequencing data.

ABSTRACT:

Summary

With the wide application of next-generation sequencing (NGS) techniques, fast tools for protein similarity search that scale well to large query datasets and large databases are highly desirable. In a previous work, we developed RAPSearch, an algorithm that achieved a ~20-90-fold speedup relative to BLAST while still achieving similar levels of sensitivity for short protein fragments derived from NGS data. RAPSearch, however, requires a substantial memory footprint to identify alignment seeds, due to its use of a suffix array data structure. Here we present RAPSearch2, a new memory-efficient implementation of the RAPSearch algorithm that uses a collision-free hash table to index a similarity search database. The utilization of an optimized data structure further speeds up

SUBMITTER: Zhao Y 

PROVIDER: S-EPMC3244761 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature